The present disclosure generally relates to systems and method for monitoring a state of a subject and, more particularly, to systems and methods for appropriate monitoring and controlling states of a subject receiving a dose of anesthetic compound(s) or, more colloquially, receiving a dose of “anesthesia” or sedation.
Although the molecular actions of many anesthetic drugs at specific receptors are known, alterations in network dynamics that disrupt information processing and produce unconsciousness have remained elusive. Typically, loss of consciousness is accompanied by increased electroencephalogram (“EEG”) power across a broad range of frequencies less than 40 Hz. Traditional analyses, including visual interpretation of EEG traces and time-frequency power spectral analysis, are computationally simple and play a central role in neurophysiology and clinical EEG applications. However, power spectral analysis treats the EEG as a collection of independent frequency bands, offering limited insight into the modulation of network activity as a whole. Because cortical networks frequently express oscillations in multiple frequency bands simultaneously, nonlinear biophysical processes, such as neuronal spiking, induce cross-frequency coupling, which is undetectable by spectral analysis. Identifying global brain states, such as sleep stages or general anesthesia-induced unconsciousness, remains a significant challenge for understanding cortical dynamics. Moreover, an EEG-based framework for understanding brain state transitions during general anesthesia will be critical for improving subject monitoring to avoid complications, such as intra-operative awareness.
Given the above, there remains a need for systems and methods that accurately characterize brain states of subjects subjected to anesthesia or sedation.